To discover the extent to which IT operations management tools are increasingly incorporating this technology, we talked to the report's author and other experts about how organizations can use cognitive search to improve IT Ops. Here are their takes on putting AI to work in IT Ops.

From enterprise search to cognitive search

One key takeaway from the report was that keyword-based search is inadequate for the data demands of today’s enterprise. Traditional enterprise search, which merely points users to the location of indexed data, tends to return incomplete or irrelevant information that users must sort through to find the solution they need--if they can find it at all.

That can be a huge productivity suck. As Gualtieri wrote in the report, "More than half (54%) of global information workers are interrupted from their work a few times or more per month to spend time looking for or trying to get access to information, insights, and answers."

With the introduction of AI technologies such as natural language processing and machine learning, enterprise search can extract more meaning from content and learn from users' searches to bring more relevant and complete results. This is similar to the way consumer search engines like Google and Bing have gotten better at interpreting what searchers are looking for based on their past behavior.

Praful Krishna, CEO of Coseer, said AI accepts queries in natural language, searches across texts, images, and databases from a single interface, and then returns with the most comprehensive yet succinct answer. Natural language search processes information at the snippet level, rather than at a document level. It then ranks these snippets based on their meaning instead of the keywords, he says.

“AI enables search as if a person read through everything and answered after understanding the meaning of what is being said.”—Praful Krishna

When AI meets IT

Gualtieri said that search related to IT Ops is different because Ops professionals are searching machine-generated rather than human-generated content. And because it's machine-generated, there are more regular patterns that can be queried to find anomalies in complex systems.

Tarun Gangwani, head of product at Grok, agrees.

"The entire IT Ops toolchain outputs valuable data on the health of their business, and AI search can provide insights on threats, such as incidents or intrusions, to IT systems."—Tarun Gangwani

For example, search operations can continuously monitor log files that provide the first clues to a misuse of the network or a bad build, he noted. Telemetry data can be scanned for anomalous activity, providing the first sign of a potential outage. "Most tools store this data in a standardized way, providing a ripe bed of information for AI tools to quickly provide unsupervised insights," Gangwani said.

Gualtieri noted that many IT Ops shops use log management tools to investigate the root cause for problems or for resource planning based on usage. But AI technologies will use historical root cause data to alert IT Ops professionals to the problem before it even happens, so they can take action to prevent it. That's a huge change that’s being directly enabled by AI, he said.

Doug Bordonaro, chief data evangelist at ThoughtSpot, explained the AI advantage in a more detailed way. "When modern AI technology is embedded in enterprise tools, it starts to become invisible. AI is no longer a feature, it's just something that happens under the hood. The average user won’t even notice—they'll just have more valuable interactions with technology."

In IT Ops, this can surface in many ways, Bordonaro continued. “Instead of running a program that tells you which assets are most at risk of failure based on age and usage, AI will tell you that by upgrading 10 percent of your older technology you'll likely end up saving 10 times the cost in labor and equipment."

Even better, this will happen without users asking the question. Log analysis changes the time-intensive task of determining structure and logic into one where the IT admin reviews insights automatically generated from the tools, he said.

"That’s a major benefit for IT ops, which can focus more on delivering unexpected insights than repetitive process.”—Doug Bordonaro

The impact of cognitive search on IT Ops

Indeed, AI promises to bring plenty of upside to the daily challenges of IT Ops. Coseer's Krishna predicted that AI-based search will ultimately automate up to 80 percent of routine IT questions.

Grok's Gangwani said IT Ops teams will ultimately spend less time managing and maintaining rules, definitions, or thresholds because cognitive search can create such relationships automatically.

Bordonaro went even further, positing that cognitive search technologies will revolutionize the very nature of IT Ops.

“Ultimately, AI-based search will make IT Ops a much less reactive discipline by shifting the focus to exceptions and insights rather than just prevention and remediation."—Bordonaro

By putting this power in the hands of people outside traditional IT—people who already know how to use a search bar—some of the responsibility can be shared with those in the organization able to take action, not just the people with the technical knowledge, Bordonaro said.

"Democratization of information, enforcement, and responsibility, while still giving IT visibility into what's happening and who has access, will give enterprises the best of both worlds—real-time, cost effective IT management without the delays and process overhead associated with tight centralization.”—Bordonaro

Those are some promising predictions. Gualtieri sees a more immediate impact that should hearten any crusty IT pro:

“IT Ops are always fighting fires and explaining why it’s not their fault. No more. AI technologies will provide them the predictive power to prevent problems before they happen.”